Lecture

Global Data Justice: Social Justice Approach to Data Governance

Related lectures (30)

Explores data ethics, focusing on fairness, justice, and Al systems' broader implications.

Covers ethical considerations in NLP, focusing on bias, toxicity, and misinformation.

Covers the Ethics and Law of AI, addressing relevant ethical and legal questions and providing insights on AI regulation.

Discusses trustworthy AI, ethical principles, and US AI regulation.

Delves into ethics and law in AI, focusing on values, normative ambitions, and ethical challenges.

Explores consequentialism, deontology, and virtue ethics, highlighting their strengths and challenges in making ethical decisions.

Explores the ethical challenges of AI, including data ethics, algorithm ethics, and societal impact.

Explores the Ethics and Law of AI, focusing on data ethics, bias, and social justice in AI systems.

Covers the ethical implications of artificial intelligence in technology, focusing on data, algorithms, design, sustainability, and accountability.

Discusses student feedback, challenges in balancing laws and ethics, and the need for more critical thinking in AI ethics.

Delves into the business impact of AI, ethical challenges, and consumer trust in technology.

Covers the fundamentals of deep learning, including data, architecture, and ethical considerations in model deployment.

Discusses the ethical implications of artificial intelligence for engineers and its regulatory context.

Explores the ethical challenges of artificial intelligence, including explainability, security, singularity, and societal impact.

Explores the legal status of the human body and detached parts, focusing on personhood, property rights, and ethical considerations.

Explores the ethical implications of AI, emphasizing transparency and accountability in its applications.

Examines historical information revolutions, ethical data concerns, automation impact, and AI ethics.

Explores advancements in generative AI and reinforcement learning, focusing on their applications, safety, and future research directions.

Explores ethical argumentation, emphasizing the duty to justify actions and the hierarchy of goods at stake in ethical dilemmas.

Explores the ethical implications of deploying machine learning algorithms and emphasizes the importance of fairness in decision-making processes.